About SwissOrthology

Orthologs are genes that have started diverging through a speciation event, and play an important role in many bioinformatics applications such as gene function prediction, species tree reconstruction or comparative analyses.

The SIB-funded initiative, SwissOrthology, is aimed at serving the orthology community— both users and method-developers. OMA (“Orthologous MAtrix”) and OrthoDB are two world wide leading resources which both provide precomputed gene orthology and stand alone software for custom orthology analyses. SwissOrthology is a joint collaboration involving both groups.

For feedback, suggestions and questions, please contact us on info@swissorthology.ch.

Maintenance and development of OMA and OrthoDB

The SwissOrthology project supports the vital maintenance and development of OMA and OrthoDB by helping of keeping both of the resources updated.

Allowing users to query both resources simultaneously

SwissOrthology provides functionality for orthology method-developers and users to retrieve consensus orthology calls derived from OMA and OrthoDB. This uses federated SPARQL queries as a backend to facilitate speedy lookups.

SwissOrthology serves as a joint interface between both resources to search for hierarchical orthologs groups for a UniProt protein.

Orthology guidance

SwissOrthology provides guidance to help prospective users determine which platform is best suited to their needs in terms of type of homologs, species, and analyses.


Though OMA and OrthoDB have distinct foci, serve different communities, and target different downstream applications, we collaborated on developing SIBLINGs, a joint effort to consolidate all-against-all homology computations on a common platform — by far the most time consuming step. The current SIBLINGs infrastructure already allows for computation of the all-against-all in a parallel, noncentralized way that can even span across different clusters. SIBLINGs is open for third party resources to adopt as the source of all-against-all gene homology data. In order to make large scale use of SIBLINGs, a group would also need to participate in computing.